Translator Disclaimer
June 2001 Asymptotics of the maximum likelihood estimator for general hidden Markov models
Randal Douc, Catherine Matias
Author Affiliations +
Bernoulli 7(3): 381-420 (June 2001).

Abstract

In this paper, we consider the consistency and asymptotic normality of the maximum likelihood estimator for a possibly non-stationary hidden Markov model where the hidden state space is a separable and compact space not necessarily finite, and both the transition kernel of the hidden chain and the conditional distribution of the observations depend on a parameter θ. For identifiable models, consistency and asymptotic normality of the maximum likelihood estimator are shown to follow from exponential memorylessness properties of the state prediction filter and geometric ergodicity of suitably extended Markov chains.

Citation

Download Citation

Randal Douc. Catherine Matias. "Asymptotics of the maximum likelihood estimator for general hidden Markov models." Bernoulli 7 (3) 381 - 420, June 2001.

Information

Published: June 2001
First available in Project Euclid: 22 March 2004

zbMATH: 0987.62018
MathSciNet: MR2002E:62081

Rights: Copyright © 2001 Bernoulli Society for Mathematical Statistics and Probability

JOURNAL ARTICLE
40 PAGES


SHARE
Vol.7 • No. 3 • June 2001
Back to Top